VGG Image Annotator (VIA)
VGG Image Annotator (VIA) is an open source image annotation tool for labeling images to create datasets for machine learning models. It supports region, rectangle, ellipse, polygon, point, and image-level annotations.
image-annotation
machine-learning
computer-vision
dataset-creation
VGG Image Annotator (VIA)
Open source image annotation tool for labeling images to create datasets for machine learning models, supporting region, rectangle, ellipse, polygon, point, and image-level annotations.
What is VGG Image Annotator (VIA)?
VGG Image Annotator (VIA) is an open source web-based image annotation tool for easily labeling images to generate datasets for machine learning and computer vision research. It allows users to mark up images with shapes like bounding boxes, circles, polygons to identify objects or regions of interest.
Some key features of VIA include:
- Annotating images by drawing polygons, rectangles, circles, ellipses etc around objects
- Image tagging with multiple region shapes
- Zooming images for precision marking
- Exporting annotations in JSON format
- Integration with several popular machine learning frameworks like TensorFlow, Keras etc.
- Support for common image formats like JPG, PNG
- Can be hosted locally without requiring server setup
Overall, VIA is lightweight and easy to use for manually creating training data. With its customizable configurations and export options, it works well with deep learning pipelines to develop computer vision models for object detection, semantic segmentation, instance segmentation etc.
VGG Image Annotator (VIA) Features
Features
- Image annotation
- Region, rectangle, ellipse, polygon and point annotations
- Image-level labels
- Keyboard shortcuts
- Project management
- Import/export annotations
- Plugin ecosystem
Pricing
- Open Source
Pros
Open source
Easy to use interface
Support for multiple annotation types
Active development community
Cross-platform
Cons
Limited documentation
Less features than some commercial options
Only supports images (no video)
No built-in data augmentation tools
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